On Tue, Dec 28, 2021 at 10:19 AM Chris Angelico wrote:
> I'm not sure about that.
>
> >>> numpy.log(2.71828)
> 0.99327347282
> >>> numpy.log([2.71828])
> array([0.9933])
> >>> type(numpy.log(2.71828))
>
> >>> type(numpy.log([2.71828]))
>
>
well, yes, there is a odd wart in numpy that
On Wed, Dec 29, 2021 at 4:54 AM Christopher Barker wrote:
>
> On Tue, Dec 28, 2021 at 5:31 AM David Mertz, Ph.D.
> wrote:
>>
>> On Tue, Dec 28, 2021 at 1:15 AM Christopher Barker
>> wrote:
>>>
>>> On Mon, Dec 27, 2021 at 4:07 PM Steven D'Aprano
Julia (if I recall correctly) has a
On Tue, Dec 28, 2021 at 5:31 AM David Mertz, Ph.D.
wrote:
> On Tue, Dec 28, 2021 at 1:15 AM Christopher Barker
> wrote:
>
>> On Mon, Dec 27, 2021 at 4:07 PM Steven D'Aprano
>>
>>> Julia (if I recall correctly) has a nice syntax for automatically
>>> turning any function or method into an
On Tue, Dec 28, 2021 at 1:15 AM Christopher Barker
wrote:
> On Mon, Dec 27, 2021 at 4:07 PM Steven D'Aprano
>
>> Julia (if I recall correctly) has a nice syntax for automatically
>> turning any function or method into an element-wise function:
>
>
> And numpy has an even easier one:
>
On Mon, Dec 27, 2021 at 07:19:12PM -, Stefan Pochmann wrote:
> Stephen J. Turnbull wrote:
> > In fact you
> > also created a whole new subordinate data flow that doesn't exist in
> > the original (the [x+1]). I bet that a complex
> > comprehension in your style will need to create a singleton
On Mon, Dec 27, 2021 at 10:15:05PM -0800, Christopher Barker wrote:
> On Mon, Dec 27, 2021 at 4:07 PM Steven D'Aprano
>
> > Julia (if I recall correctly) has a nice syntax for automatically
> > turning any function or method into an element-wise function:
>
>
> And numpy has an even easier one:
Steven D'Aprano writes:
> I believe that Serhiy has optimized the case where a comprehension loops
> over a singleton list or tuple.
Yeah, I missed that.
> > We are well-used to reading parenthesized expressions, though.
>
> Just because we're used to them doesn't make them easy to read.
